The principal investigator has developed a mathematical statistic, ApEn, to analyze time-series data. The long term objective of this proposal is to examine the potential use of ApEn as a biomarker of aging, to predict adverse consequences of autonomic dysfunction, such as hypotension and syncope, and to evaluate such interventions as exercise and medication. It is anticipated that ApEn, applied to heart rate and blood pressure data, will provide diagnostic and predictive insights otherwise unavailable. ApEn is both mathematically and medically innovative. It encapsulates the amount of patternness in data into a single number. Advantages over alternative approaches include objectivity, ready computability, breadth of focus, and potential for immediate applicability. Several prototype studies have already demonstrated the efficacy of ApEn. Phase I focuses on determining whether ApEn shows a significant decline with increasing age for heart rate and blood pressure data. A Phase II study would establish definitive ranges of ApEn values, for each age group, as normative or as indicative of autonomic dysfunction. Longitudinal studies would determine ApEn's ability to evaluate interventions to reverse dysfunction. Potential commercial applications include a software package to compute ApEn for use in existing systems or in a solo device.